U.S. patent number 10,201,314 [Application Number 14/389,400] was granted by the patent office on 2019-02-12 for system and method for evaluation of circulatory function.
This patent grant is currently assigned to MCLEAN HOSPITAL CORPORATION. The grantee listed for this patent is Blaise Frederick, Lia Maria Hocke, Yunjie Tong. Invention is credited to Blaise Frederick, Lia Maria Hocke, Yunjie Tong.
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United States Patent |
10,201,314 |
Frederick , et al. |
February 12, 2019 |
System and method for evaluation of circulatory function
Abstract
A system and method for evaluating a circulatory function of an
individual includes at least one connection configured to receive
signals indicative of functional data relating to at least one
functional parameter of the cardiovascular system of the subject
and to at least two disparate locations on the subject. A processor
is coupled to the at least, one connection and configured to
receive the functional data from the at least one connection. The
processor is also configured to compare the functional data to
identify variations that deviate from an expected delay associated
with the disparate locations and provide an assessment of the
cardiovascular system function based on the comparison of the
functional data.
Inventors: |
Frederick; Blaise (Belmont,
MA), Hocke; Lia Maria (Medford, MA), Tong; Yunjie
(Medford, MA) |
Applicant: |
Name |
City |
State |
Country |
Type |
Frederick; Blaise
Hocke; Lia Maria
Tong; Yunjie |
Belmont
Medford
Medford |
MA
MA
MA |
US
US
US |
|
|
Assignee: |
MCLEAN HOSPITAL CORPORATION
(Belmont, MA)
|
Family
ID: |
49301006 |
Appl.
No.: |
14/389,400 |
Filed: |
April 3, 2013 |
PCT
Filed: |
April 03, 2013 |
PCT No.: |
PCT/US2013/035061 |
371(c)(1),(2),(4) Date: |
September 30, 2014 |
PCT
Pub. No.: |
WO2013/152066 |
PCT
Pub. Date: |
October 10, 2013 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20150065827 A1 |
Mar 5, 2015 |
|
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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61619471 |
Apr 3, 2012 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B
5/14551 (20130101); A61B 5/7246 (20130101); A61B
5/0205 (20130101); A61B 5/6826 (20130101); A61B
5/1455 (20130101); A61B 5/0261 (20130101); A61B
5/7282 (20130101); A61B 5/7253 (20130101); A61B
5/021 (20130101); A61B 5/14546 (20130101); A61B
2562/04 (20130101) |
Current International
Class: |
A61B
5/1455 (20060101); A61B 5/00 (20060101); A61B
5/145 (20060101); A61B 5/026 (20060101); A61B
5/021 (20060101); A61B 5/0205 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Other References
International Search Report and Written Opinion dated Jun. 24, 2013
in connection with PCT/US2013/035061. cited by applicant.
|
Primary Examiner: Winakur; Eric
Assistant Examiner: Fardanesh; Marjan
Attorney, Agent or Firm: Quarles & Brady LLP
Government Interests
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH
This invention was made with Government support under Grant Number
DA027877 awarded by the National Institutes of Health. The
Government has certain rights in this invention.
Parent Case Text
CROSS-REFERENCE TO RELATED APPLICATIONS
This application represents the national stage entry of PCT
International Application No. PCT/US2013/035061 filed Apr. 3, 2013,
which claims priority to U.S. Provisional Application Ser. No.
61/619,471, filed Apr. 3, 2012, both of which are hereby
incorporated herein by reference for all purposes.
Claims
The invention claimed is:
1. A system configured to analyze cardiovascular system function of
a subject, the system comprising: at least one connection
configured to receive signals indicative of data relating to at
least one parameter of the cardiovascular system of the subject and
to at least two disparate locations on the subject; a processor
coupled to the at least one connection and configured to: receive
the data from the at least one connection; transform the data into
timecourses of monitored metrics associated with respective the
disparate locations; filter the timecourses into a predetermined
number of frequency bands, wherein at least one of the frequency
bands includes frequencies corresponding to a low frequency
oscillations (LFO) band; analyze the timecourses after filtering to
identify variations that deviate from an expected delay associated
with the disparate locations; and generate an assessment report of
the cardiovascular system function based on the analysis of the
timecourses after filtering.
2. The system of claim 1 further comprising at least two sensors
configured to derive the data from the subject and connected to the
at least one connection to communicate the signals.
3. The system of claim 1 wherein the processor is further
configured to determine, from the data, at least one of endogenous
fluctuations in oxygenation and concentration levels at the
disparate locations.
4. The system of claim 3 wherein the processor is further
configured to determine a relative strength and propagation delay
of at least one of blood flow and the pressure waves associated
with the endogenous fluctuations.
5. The system of claim 1 wherein the processor is further
configured to perform a Modified Beer-Lambert law transform to the
data.
6. The system of claim 1 wherein at least one of the frequency
bands includes frequencies corresponding to a cardiac band.
7. The system of claim 1 further comprising at least one sensor
connected to the at least one connection and in communication with
the processor, the processor configured to differentiate oxy and
deoxy hemoglobin within the cardiovascular system.
8. The system of claim 1 wherein the processor is configured to
determine at least one of a speed of bulk average blood flow and a
speed of wave propagation through blood within the cardiovascular
system from the data to identify variations that deviate from the
expected delay associated with the disparate locations.
9. The system of claim 1 wherein the processor is further
configured to determine a phase value at each of a plurality of
frequencies in the data to determine a time delay between the data
and indicate the time delay to provide the assessment of the
cardiovascular system function.
10. A system configured to analyze cardiovascular system function
of a subject, the system comprising: at least two sensors located
at disparate locations on the subject and configured to acquire
data relating to at least one parameter of the cardiovascular
system of the subject at the disparate locations; a processor
configured to: receive the data from the at least two sensors;
assemble the data into respective waveforms associated with
respective disparate locations of the at least two sensors;
transform the data into timecourses of monitored metrics associated
with respective the disparate locations; filter the timecourses
into a predetermined number of frequency bands, wherein at least
one of the frequency bands includes frequencies corresponding to a
low frequency oscillations (LFO) band; analyze the timecourses
after filtering to identify variations between the waveforms that
deviate from an expected delay associated with the disparate
locations; and generate an assessment report of the cardiovascular
system function based on the analysis of the timecourses after
filtering.
11. The system of claim 10 wherein the processor is further
configured to transform the data into respective timecourses of
monitored metrics associated with respective ones of the at least
two sensors and the associated disparate locations.
12. The system of claim 11 wherein the processor is further
configured to perform a Modified Beer-Lambert law transform to the
data.
13. The system of claim 10 wherein at least one of the frequency
bands includes frequencies corresponding to a cardiac band.
14. The system of claim 10 wherein the at least two sensors are in
communication with the processor, the processor configured to
differentiate oxy and deoxy hemoglobin within the cardiovascular
system.
15. The system of claim 14 wherein the processor is further
configured to estimate a variation in concentration of at least one
of oxy hemoglobin, deoxy hemoglobin, and total hemoglobin to
determine temporal changes in blood parameters.
16. The system of claim 10 wherein the data includes temporal
changes in blood parameters.
17. The system of claim 10 wherein the processor is configured to
determine at least one of a speed of bulk average blood flow and a
speed of wave propagation through blood within the cardiovascular
system from the data to identify variations between the waveforms
that deviate from an expected delay associated with the disparate
locations.
18. The system of claim 10 wherein the processor is further
configured to determine a temporal crosscorrelation between the
waveforms taking into consideration the disparate locations of the
at least two sensor to determine a degree of similarity between the
waveforms as a function of delay time and indicate the similarity
between the waveforms as the function of delay time to provide the
assessment of the cardiovascular system function.
19. The system of claim 10 wherein the processor is further
configured to determine a phase value at each of a plurality of
frequencies in the waveforms to determine a time delay between the
waveforms and indicate the time delay to provide the assessment of
the cardiovascular system function.
20. The system of claim 10 wherein the at least two sensors include
near-infrared spectroscopy (NIRS) sensors.
21. The system of claim 10 wherein the disparate locations include
fingers of opposing hands.
22. A method for evaluating a circulatory function of an
individual, comprising: capturing, at a first location on the
individual, a first dataset from a first sensor configured to
detect blood flow fluctuations at frequencies corresponding to low
frequency oscillations (LFO); capturing, at a second location on
the individual, a second dataset from a second sensor configured to
detect blood flow fluctuations at frequencies corresponding to LFO;
determining a temporal shift between the first dataset and the
second dataset; and generating a report, using the determined
temporal shift, identifying a circulatory dysfunction in the
individual.
23. The method of claim 22 wherein the blood flow fluctuations
include cardiac band fluctuations.
24. The method of claim 22 wherein the first sensor is a
near-infrared spectroscopy (NIRS) and the second sensor is an NIRS
sensor.
25. The method of claim 22 including transforming the first and
second dataset using a modified Beer-Lambert law.
26. The method of claim 25 including converting timecourses of the
first and second transformed datasets into frequency bands, wherein
at least one of the frequency bands includes frequencies
corresponding to the LFO.
27. The method of claim 22 wherein determining the temporal shift
includes at least one of: i) determining a temporal
crosscorrelation between the first dataset and the second dataset
to determine a degree of similarity between the first dataset and
the second dataset; and ii) determining a phase value at each of a
plurality of frequencies in the first dataset and the second
dataset to determine a time delay between the first dataset and the
second dataset.
Description
BACKGROUND OF THE INVENTION
The present invention relates generally to systems and methods for
the evaluation of a circulatory function and, more particularly, to
systems and methods for analyzing propagation of blood stream
attributes through a circulatory system to identify an attribute
thereof and, thereby, acquire clinically useful information about a
subject.
In an individual, a large number of conditions can result in poor
operation of and blood flow through the circulatory system. Example
conditions include, but are not limited to, vessel occlusion, loss
of muscular tone, edema, arterial hardening, peripheral arterial
disease, artherosclerosis, abnormal sympathetic or parasympathetic
function, and cerebral or autonomic dysfunction.
In many cases, to diagnose these conditions by the analysis of
blood flow through an individual, it is necessary to use expensive
imaging equipment to detect and/or quantify an ineffective
operation of the circulatory system, or highly trained personnel,
or both. For example, imaging devices such magnetic resonance
imaging (MRI) systems can be used, such as to perform so-called
functional MRI (fMRI) procedures that rely on the as
blood-oxygen-level-dependent (BOLD) contrast mechanism, to acquire
indirect information about the flow of blood through a subject. As
another example, an MRI system can be used in conjunction with an
injected contrast agent that flows through and can be imaged within
the vasculature to identify abnormal attributes of blood flow
through an individual's circulatory system. Using these images,
clinicians attempt to trace the abnormal attributes to a particular
condition. Unfortunately, these imaging systems are expensive and
complicated to operate making the diagnosis of a condition by these
methods expensive and time consuming. Furthermore, in the case of
so-called contrast enhanced MRI studies that rely on the injection
of a gadolinium-based contrast agent, there are clinical
indications and scientific evidence that the contrast agent,
itself, can be extremely harmful to a sub-section of the population
and, in the case of nephrogenic systemic fibrosis, deadly. Other
methods include the use of injected radioactive tracer materials,
which carry their own risks and expense. Other methods, such as
ankle brachial index (ABI) measurements, require trained operators,
and manipulations of blood flow with pressure cuffs which may be
difficult or impossible in some patient groups, such as the
obese.
These existing methods also are measurements at a single point of
time, and in most cases require moving the subject to a procedure
room. These methods cannot be used for continuous circulatory
monitoring, or monitoring at home, for example.
Therefore, it would be desirable to have alternative or even
complementary systems and methods for evaluating the performance of
a subject's circulatory system, particularly, systems and methods
that are more widely available and more cost effective than
expensive imaging modalities, such as MRI and radionuclide methods,
and is free of associated health risks, and systems that can
measure circulation passively, continuously, and/or
automatically.
SUMMARY OF THE INVENTION
The present invention overcomes the aforementioned drawbacks by
providing systems and methods for evaluation of a circulatory
function using readily-available and fairly-inexpensive
technologies, such as optical imaging. More particularly, the
present invention provides systems and methods for analyzing
propagation of blood stream attributes to derive clinically useful
information about the subject and the current operation of the
subject's circulatory system.
In accordance with one aspect of the invention, a system is
disclosed that is configured to analyze cardiovascular system
function of a subject. The system includes at least one connection
configured to receive signals indicative of functional data
relating to at least one functional parameter of the cardiovascular
system of the subject and to at least two disparate locations on
the subject. The system also includes a processor coupled to the at
least one connection and configured to receive the functional data
from the at least one connection and compare the functional data to
identify variations that deviate from an expected delay associated
with the disparate locations. The processor is also configured to
provide an assessment of the cardiovascular system function based
on the comparison of the functional data.
In accordance with another aspect of the invention, a system
configured to analyze cardiovascular system function of a subject
is disclosed that includes at least two sensors located at
disparate locations on the subject and configured to acquire
functional data relating to at least one functional parameter of
the cardiovascular system of the subject at the disparate
locations. The system also includes a processor configured to
receive the functional data from the at least two sensors and
assemble the functional data into respective waveforms associated
with respective disparate locations of the at least two sensors.
The processor is further configured to compare the waveforms to
identify variations between the waveforms that deviate from an
expected delay associated with the disparate locations and provide
an assessment of the cardiovascular system function based on the
comparison of the waveforms.
In accordance with yet another aspect of the invention, a method
for evaluating a circulatory function of an individual is disclosed
that includes capturing a first dataset from a first sensor
configured to detect blood flow fluctuations at a first location on
the individual. A second dataset is captured from a second sensor
configured to detect blood flow fluctuations at a second location
on the individual. A temporal shift is determined between the first
dataset and the second dataset and a report is generated, using the
determined temporal shift that identifies a circulatory dysfunction
in the individual.
The foregoing and other aspects of the invention will appear from
the following description. In the description, reference is made to
the accompanying drawings which form a part hereof, and in which
there is shown by way of illustration a preferred embodiment of the
invention. Such embodiment does not necessarily represent the full
scope of the invention, however, and reference is made therefore to
the claims and herein for interpreting the scope of the
invention.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is an illustration of a differential monitoring system in
accordance with the present invention that, in the illustrated
configuration, utilizes a pulse oximeter to monitor attributes of
an individual's blood flow.
FIG. 2 is a schematic diagram showing functional components of the
present system for evaluating the circulatory function of an
individual.
FIG. 3 is a flowchart setting forth exemplary steps of a method for
analyzing data from a differential monitoring system positioned on
an individual to identify a circulatory dysfunction.
FIGS. 4A-E illustrate an exemplary sensor configuration and
associated reports generated with the exemplary sensor
configuration.
DETAILED DESCRIPTION OF THE INVENTION
The present invention recognizes that, at a particular location in
an individual's circulatory system, blood oxygenation and
concentration levels naturally fluctuate on a variety of
timescales. A first set of fluctuations, referred to as
low-frequency oscillations (LFOs), oscillate in the range of
approximately 0.01 Hertz (Hz) to 0.15 Hz. A second set of
fluctuations, referred to as cardiac band fluctuations, oscillate
in the range of approximately 0.7 Hz to 3 Hz. A third set of
fluctuations, referred to as respiratory fluctuations, oscillate in
the range of approximately 0.2 Hz to 0.67 Hz.
It has been determined that these fluctuations are carried or
communicated through the blood stream as the blood circulates
throughout the individual's body. The fluctuations are carried both
in the blood itself, as well as in pressure waves that travel
through the blood. Deficiencies in the individual's circulatory
system can cause the arrival time of these various fluctuations at
different locations of the body to vary or otherwise deviate from
an expected tolerance. These endogenous fluctuations in oxygenation
and concentration levels can be detected at different locations as
they travel via the individual's blood stream. By comparing signals
acquired from different locations of the body, the relative
strength and propagation delay of the blood and the pressure waves
associated with the fluctuations can be compared.
The present invention further recognizes that the detected
propagation delays and signal strengths carry information about the
condition of the blood stream supplying each location and,
furthermore, this information can be used to determine
characteristics of the blood vessels and the blood content of the
individual. Consequently, the present invention recognizes that a
comparison of the signals detected at different locations of the
body can be used to provide diagnostic information about
circulatory function and/or pathology in the individual.
One technique for monitoring particular characteristics of blood
flowing within the body is near-infrared spectroscopy (NIRS). NIRS
is a method of spectroscopy that exploits the absorptivity of
certain substances in the near-infrared region to identify the
contents of materials, such as blood. NIRS can be used to identify
the contents (e.g., blood sugar levels) of blood, as well as
blood-oxygen characteristics and changes in blood volume. In these
conventional uses of NIRS, highly-localized information, such as
provided by a NIRS monitor located on an individual's finger, is
gathered and characteristics of the blood flowing through that
highly-localized area is determined, such as the blood sugar or
oxygenation of blood in that finger. However, as will be described,
the present invention recognizes that NIRS and other monitoring
mechanisms and systems can be used to monitor fluctuations in
oxygenation and concentration, as well as other properties, in the
blood stream at a local level, but also to couple such measurements
into non-local and even global systems. For example, when
configured into differential diagnosis systems, the present
invention includes analysis systems and methods so that data can be
generated regarding wide-scale circulatory function and
dysfunction.
For example, referring to FIG. 1, pulse oximeters are devices that
use NIRS to monitor characteristics of an individual's circulation.
FIG. 1, for example, shows a system using a pulse oximeter to
monitor attributes of an individual. As shown in FIG. 1, a system
100 includes a sensor 110, a monitor 120, and a cable 140
connecting the sensor 110 and the monitor 120. In accordance with
the present invention, the cable 140 may include multiple branches
142 and 144. In this regard, the illustrated sensor 110 is
connected to one location on the individual, such as the fingertip
10. Though omitted from FIG. 1 for simplicity, a sensor similar to
that of the illustrated sensor 110 is located at a terminal end of
branch 144 to monitor another fingertip, such as located on the
individual's right hand, or any of a wide variety of other
locations on the individual, such as the foot, neck, and the
like.
Referring to FIGS. 1 and 2, the sensors 110 and 110' may have
optical emitters 112 and 112' and detectors 114 and 114' and each
attached to an individual at a selected fleshy medium site, such as
a fingertip 10, as shown, or a toe or an ear lobe. For example, the
sensors 110 and 110' may be continuous blood pressure monitoring
sensors or other sensors, such as will be described. The emitters
112 and 112' are positioned to project light of through the blood
vessels and capillaries of the fleshy medium. The detectors 114 and
114' are positioned to detect the emitted light after absorption
and scattering by the fleshy medium, including hemoglobin and other
constituents of pulsatile blood flowing within the fleshy medium,
and generate signals corresponding to the intensity of the emitted
light.
For example, each sensor 110 and 110' may be configured to measure
the transmission and/or reflectance of one or more wavelengths of
light in the red or near infrared spectrum (e.g., of wavelengths
from approximately 650 nanometers (nm) to 1100 nm) in a tissue
sample. The sensors 110 and 110' may, for example, illuminate
tissue with one or more wavelengths of light and record the light
incident on one or more photodetectors that capture light emitted
from that tissue.
The sensors 110 and 110' can illuminate the tissue in a continuous
or time varying fashion, depending on the particular design of the
sensor or probe. The time variation in tissue reflectance and/or
transmission can be measurable at the frequency or frequencies of
interest. Example frequencies of interest include the LFO band, the
cardiac band, the respiratory band, and combinations thereof. The
captured signals can be processed further (for example, by monitor
120) or may be recorded for later analysis.
The monitor 120, which may be a standalone device or may be
incorporated as a module or built-in portion of a multiparameter
monitoring system, computes at least one physiological parameter
responsive to the signals acquired by the sensors 110 and 110',
such as magnitudes of detected intensity signals. The monitor 120
can provide a numerical readout of the individual's oxygen
saturation 122, a numerical readout of pulse rate 124, and a
display of the patient's plethysmograph 126, which provides a
visual display of the patient's pulse contour and pulse rate, and
other parameters, for example, such as the relative strength of
signals in various bands, such as the cardiac and LFO bands.
In the system of the present invention, a processor 150 is
provided, which by way only of example may be included in the
monitor 120. Also, a memory 160 may be coupled to the processor
150. The memory 160 stores instructions that cause the processor to
execute methods, such as will be described in greater detail
below.
The signals captured from any of the sensors 110 and 110' can be
used directly by the processor 150, or may transformed using
various formulae before performing further analysis. The sensors
110 and 110' are configured to measure fluctuations in local
hemodynamic parameters in various frequency ranges and the
processor 150 may be programmed to determine a variety of
time-varying characteristics or metrics. A portion of the
hemodynamic signal detected by the sensors 110 and 110' at various
locations on the individual's body results from the global
oxygenation and concentration signal passing through the sensitive
region of the sensor's optical probe. The processor 150 can
determine the degree of global signal shared between the sensors
110 and 110' using a cross-correlation function. The maximum
amplitude of the correlation function indicates the degree of
shared signal, and the time lag of the maximum amplitude of the
correlation function indicates the difference in arrival time of
the signals at the location of the two sensor 110 and 110', and
whether one signal lags or leads the other.
In accordance with the present invention, by comparing the times at
which each sensor 110 and 110' detects particular fluctuations in
the individual's blood flow, the processor 150 is able to
characterize attributes of the individual's circulatory system,
such as time delays or correlation strengths, thereby providing
clinical information to aid in diagnosing a condition resulting in
circulatory dysfunction.
The calculated time delays and/or correlation strengths in one or
more frequency bands between one or more sensors, or the changes in
those measured during or between exams, or relative to
predetermined values, can be presented numerically or graphically
on a display provided by the monitor 120 or other display system,
and/or analyzed automatically and compared to expected values,
and/or recorded for later analysis.
For example, the above-described system may be used as a diagnostic
system for assessing peripheral arterial blockage and for
monitoring patients during/after peripheral angioplasty or
peripheral bypass surgery.
Referring to FIG. 3, a flowchart is provided illustrating a method
300 for analyzing waveforms captured from two or more sensors
positioned on an individual to identify a circulatory dysfunction.
In step 302, two or more sensors, such as NIRS sensors, are
positioned on the individual's body, generally at disparate
locations, such as fingers of opposing hands or the like. When
using a sensor pair, the sensors may be positioned on the
individual's fingers and toes, or fingers on both hands, or toes on
different feet, or different locations on the head, or between a
location on the head and on a finger or toe, or a finger and over a
major muscle, for example. That is, the sensors do not need to be
on different limbs or regions, but should positioned to monitor
regions supplied by different portions of the vasculature. For
example, if trying to diagnose a circulatory dysfunction in a
single finger, two adjacent fingers can be monitored. Fingers and
toes are provided as examples because they are convenient locations
for sensor and have very different vascular sources. As such, they
can be advantageous for certain clinical applications, such as
diagnosing circulatory problems in diabetes, because positions far
from the heart at the end of long arterial paths provide clean
indications of such problems. However, if the duration for
recording data is not of consequence, even extremely close sensors
can provide suitable differential data.
In step 304, after the sensors are positioned, data is collected,
for example, in the form of time-varying waveforms. For example, in
the case of NIRS sensors the data may be representative of
multi-wavelength red/near-infrared spectroscopic waveforms, for
example, including two wavelengths of approximately 690 nm and 830
nm. These or other wavelengths may be selected to differentiate a
characteristic of blood, such as differentiation of oxy and deoxy
hemoglobin within the individual's bloodstream. In other
implementations, only a single infrared wavelength (for example, of
approximately 830 nm) is captured if there is no requirement to
consider species separately, but additional wavelengths generally
provide additional independent measures resulting in an improved
signal to noise ratio (SNR) in the captured data. By increasing the
SNR, shorter measurement times, and improved differentiation of oxy
and deoxy hemoglobin can be achieved, so that the identification of
different types of circulatory dysfunction may be facilitated.
After the waveforms are captured, in step 306 the waveforms are
converted to a timecourse of monitored metrics. For example, raw
optical measurements may be converted to measurements of the
changes in oxy and deoxy hemoglobin, for example, using a Modified
Beer-Lambert law transform. By way of the transform or associated
processing the captured signals may be used to derive estimates of
the variation in concentration of oxyhemoglobin and/or
deoxyhemoglobin, and/or total hemoglobin, or some other parameter
that reflects temporal changes in blood parameters. In one
implementation of the present system, oxyhemoglobin and total
hemoglobin waveforms are derived for analysis. The Modified
Beer-Lambert law transform is mentioned here because it is well
known and computationally inexpensive. Other transforms can be
used, or no transform at all. If multidistance optical measurements
are made at each recording site, more sophisticated processing can
be used to calculate absolute (rather than relative) oxy- and
deoxy-hemoglobin concentration waveforms, which would provide
additional diagnostic information. In other implementations of the
system, though, no transformation is necessary. In that case, the
captured raw waveforms can be analyzed directly to observe temporal
variation in the captured signals using the raw optical signal. The
temporal variation can then be used to identify circulatory
dysfunction, as described below. However, by performing the
transformation of step 306, or other transforms, it may be possible
to improve the SNR in the captured data using covarying to remove
some irrelevant measurement factors.
In optional step 308, the timecourse of monitored metrics may be
filtered into a number of relevant frequency bands. In one
implementation, for example, the timecourses are filtered into the
LFO band and the cardiac band. These bands are variably defined in
literature, but the LFO band generally occurs between approximately
0.01 Hz and 0.15 Hz. The cardiac band, which captures the heartbeat
waveform and a few harmonics, so the shape will not be overly
distorted, generally occurs between approximately 0.7 Hz and 4.0
Hz.
It has been observed that portions of the time variation of the oxy
and deoxy hemoglobin concentrations propagate through the
bloodstream at two dominant speeds--the speed of bulk average blood
flow, and the speed of wave propagation through the blood.
Generally, the LFO signal travels at the speed of average bulk
flow, while the cardiac signal travels at the wave propagation
speed. As a result, there will be variable timeshifts between the
LFO signal and the cardiac signal in different measurement sites
throughout the body. By quantifying the amount of global signal in
each frequency band at each location, and the relative timeshifts
between locations (and between frequency bands), it is possible to
infer properties of the circulatory system.
The present method may use either of at least two alternative
methods to analyze the captured signals to determine properties of
the circulatory system.
In step 310, the system can use the temporal cross-correlation
between a pair of LFO signals or pair of cardiac signals generated
at different locations on the individual to determine a degree of
similarity between the signals as a function of delay time. A
cross-correlation function provides a method of estimating the
similarity of two signals and the time delay between those signals.
The time delay between the signals can be averaged over time or
calculated over multiple (perhaps overlapping) time periods to
capture dynamic variation in hemodynamics, either at rest, or in
response to some action on the part of the subject or some
intervention (e.g. changing body orientation, performing a mental
or physical action, changing breathing pattern, occlusion of a
blood vessel, and the like).
The correlation function in different frequency bands can be used
to identify a number of blood propagation parameters. For example,
because the LFO signal appears to primarily move with the blood
itself, the LFO signal allows estimation of the relative arrival
times of blood at different regions of the body by examining the
cross-correlation of the LFO signals at the locations of the
sensors. The cardiac fluctuation signal, however, travels as a
pressure wave through the vasculature, moving faster than the blood
carrying the fluctuation. As a result, a dedicated cardiac signal,
such as from an electrocardiogram (EEG) may, optionally, be
acquired at step 311. Regardless of whether separately acquired or
derived from the optical data, the cross-correlation of the cardiac
signals may be derived to yield further information about the
differences in pressure wave propagation speed.
The delay time may correspond to the temporal shift between points
of maximum similarity (i.e., highest correlation coefficient)
between the two locations. The amplitude of the correlation
coefficient at that time delay indicates the degree of shared
signal between the locations. The shape of the peak (e.g., the
width and asymmetry) can also be analyzed to determine attributes
of the individual's blood vessels nearby the sensor locations.
Broader peaks, for example, may indicate increased drag in the
vessels leading to one or the other sensor location.
Delay times between different sensor pairs may indicate pathology.
For example, preliminary data acquired in healthy subjects
indicates that the LFO signal in the left big toe lags the signal
in the left index finger by 2.5-4 seconds. A delay time
significantly longer than this may indicate impaired circulation to
the left leg, which may be a result of a chronic condition such as
arterial blockage or circulatory problems associated with diabetes.
Similarly, if the delay is greater than 0.5-1 second between two
sensors placed on fingers of opposite hands, that may indicate
thoracic outlet syndrome.
Additionally or alternatively, in step 312, the system may
calculate the coherence of a pair of signals captured from the
sensors. The coherence carries the same types of information as the
cross-correlation, described above, but in the spectral domain.
Accordingly, a similar analysis may be made of the coherence of the
two signals to determine temporal shift between sensor locations
that, as described above, are indicative of an attribute of the
individual's blood vessel.
In step 312, it is not necessary to split the captured data into
bands before comparing the two signals as the similarity between
signals is indicated as a function of frequency, and the phase
value at each frequency location gives and indication of time
delay.
Other techniques for filtering the data captured from the sensors
include using time domain or Fourier domain bandpass filter (e.g.,
0.01 Hz<LFO<0.15 Hz). The two derived LFO signals can then be
cross-correlated in order to calculate the maximum correlation and
corresponding temporal shifts between these two signals.
When implementing the above-described method 300, the relative
blood arrival times of different fluctuations are determined at
different locations on an individual. It should be noted that this
approach is not simply calculating propagation delays between two
locations on the individual. Because all blood going to the
individual's periphery comes from the left ventricle through the
aorta, that is the probable source region for the blood flow.
Accordingly, the time differences detected represent the difference
in arrival time from the aorta to the tissue of interest. Given the
aorta's depth, it is difficult to make a pure NIRS measurement of
the signal in the aorta from outside the body, though in some
circumstances this may be possible using a catheter or an
endoscopic probe. In some implementations, as described above, for
example with respect to step 311, the heartbeat signal could be
detected using an electrocardiography (EKG) system to determine
absolute wave propagation time.
Taking these considerations of the disparate locations of the
sensors and the implications of general heart function with respect
to the disparate locations, the process ends at step 314 with the
generation of a report on the cardiovascular function of the
subject being monitored. For example, the generated report may
simply be a waveform, such as could be communicated via a display
on the monitor 120 of FIG. 1. Other reports may include detailed
written or printed reports, auditory or visual alerts and the
like.
The present system may be implemented as a set of NIRS probes
clipped to a finger on each hand of an individual, a toe on each
foot, one toe and one finger, and one or more locations on the
scalp to record signals simultaneously. The captured signals can
then be compared. This technique or equipment would provide a
relatively inexpensive method for measuring circulatory dysfunction
that may be caused by, for example, inadequate or compromised
perfusion of peripheral or other tissue either chronically, for
example due to diabetes or obstructive artery disease, or acutely
as the result of an injury or intervention; abnormalities in
relative blood arrival time, which may signal arterial blockage,
venous prolapse, or other circulatory problems such as stroke or
carotid occlusion. Further, differential blood arrival times may be
affected by abnormal vascularization, such as in tumors or
arteriovenous malformations or shunts.
For example, referring now to FIGS. 4A and 4B, an exemplary system
is illustrated with the exemplary placement of the NIRS probes on
the middle fingertip (FIG. 4A) and the big toe (FIG. 4B). FIG. 4C
illustrates one exemplary report of temporal traces of .DELTA.[HbO]
obtained by the NIRS at the fingertip and left toe. FIG. 4D
illustrates an enlarged section of FIG. 4C (indicated by gray
block). The LFO signal of the finger and toe from, elucidate that
the signal measured at the toe is 2.72 s later than that of the
finger, as best illustrated in FIG. 4E. Time is given in TR
(repetition time in fMRI).
Alternatively, the system can use one or more NIRS source detector
pairs located some distance apart, where one or more of the
detectors are inserted into one or more blood vessels with a
catheter. Differential timing of the signals detected by the NIRS
sensors can be used to measure blood velocity and propagation
directly.
In some implementations of the device, one or more of the NIRS
probes can use multiple source-detector distances at a location to
provide absolute measurement of hemoglobin concentrations.
Some of the functional units described in this specification have
been described as modules in order to more particularly emphasize
their implementation. For example, a "module" including the
monitor, processor, and memory was described. However, a module may
be implemented in a hardware circuit or may be separated or
distributed. Modules may also be implemented in software for
execution by various types of processors. An identified module of
executable code may, for example, comprise one or more physical or
logical blocks of computer instructions which may, for example, be
organized as an object, procedure, or function. Nevertheless, the
executables of an identified module need not be physically located
together, but may comprise disparate instructions stored in
different locations which, when joined logically together, comprise
the module and achieve the stated purpose for the module.
The schematic flow chart diagrams included are generally set forth
as logical flow chart diagrams. As such, the depicted order and
labeled steps are indicative of one embodiment of the presented
method. Other steps and methods may be conceived that are
equivalent in function, logic, or effect to one or more steps, or
portions thereof, of the illustrated method. Additionally, the
format and symbols employed are provided to explain the logical
steps of the method and are understood not to limit the scope of
the method. Although various arrow types and line types may be
employed in the flow chart diagrams, they are understood not to
limit the scope of the corresponding method. Indeed, some arrows or
other connectors may be used to indicate only the logical flow of
the method. For instance, an arrow may indicate a waiting or
monitoring period of unspecified duration between enumerated steps
of the depicted method. Additionally, the order in which a
particular method occurs may or may not strictly adhere to the
order of the corresponding steps shown.
Furthermore, the described features, structures, or characteristics
of the invention may be combined in any suitable manner in one or
more embodiments. In the following description, numerous specific
details are provided to provide a thorough understanding of
embodiments of the invention. One skilled in the relevant art will
recognize, however, that the invention may be practiced without one
or more of the specific details, or with other methods, components,
materials, and so forth. In other instances, well-known structures,
materials, or operations are not shown or described in detail to
avoid obscuring aspects of the invention.
This invention is described in preferred embodiments in the
following description with reference to the Figures, in which like
numbers represent the same or similar elements. Reference
throughout this specification to "one embodiment," "an embodiment,"
or similar language means that a particular feature, structure, or
characteristic described in connection with the embodiment is
included in at least one embodiment of the present invention. Thus,
appearances of the phrases "in one embodiment," "in an embodiment,"
and similar language throughout this specification may, but do not
necessarily, all refer to the same embodiment.
Where, "data storage media," or "computer readable media" is used,
Applicants mean an information storage medium in combination with
the hardware, firmware, and/or software, needed to write
information to, and read information from, that information storage
medium.
The present invention has been described in terms of one or more
preferred embodiments, and it should be appreciated that many
equivalents, alternatives, variations, and modifications, aside
from those expressly stated, are possible and within the scope of
the invention.
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